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Assessing the response to oncological treatments is paramount for determining the prognosis and defining the best treatment for each patient. Several biomarkers, including imaging, can be used, but standardization is fundamental for consistency and reliability. Tumor response evaluation criteria have been defined by international groups for application in pharmaceutical clinical trials evaluating new drugs or therapeutic strategies. RECIST 1.1 criteria are exclusively based on unidimensional lesion measurements; changes in tumor size are used as surrogate imaging biomarkers to correlate with patient outcomes. However, increased tumor size does not always reflect tumor progression. The introduction of immunotherapy has led to the development of new criteria (iRECIST, Level of Evidence (LoE) Ib) that consider the possibility that an increase in disease burden is secondary to the immune response instead of progression, with the new concept of Unconfirmed Progressive Disease (a first progression event which must be confirmed on follow-up). Specific criteria were devised for HCC (mRECIST, LoE IV), which measure only enhancing HCC portions to account for changes after local therapy. For GIST treated with imatinib, criteria were developed to account for the possible increase in size reflecting a response rather than a progression by assessing both tumor size and density on CT (Choi, LoE II). This article provides concise and relevant practice recommendations aimed at general radiologists to help choose and apply the most appropriate criteria for assessing response to treatment in different oncologic scenarios. Though these criteria were developed for clinical trials, they may be applied in clinical practice as a guide for day-to-day interpretation. KEY POINTS: Response evaluation criteria, designed for use in clinical trials, might serve as a surrogate biomarker for overall survival. RECIST 1.1 defines measurable and non-measurable disease among which target lesions and non-target lesions are selected at baseline as reference for follow-ups. Some therapies and/or cancers require the use of different criteria, such as iRECIST, mRECIST, and Choi criteria.
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We aim to develop a deep learning-based algorithm for automated segmentation of thigh muscles and subcutaneous adipose tissue (SAT) from T1-weighted muscle MRIs from patients affected by muscular dystrophies (MDs). From March 2019 to February 2022, adult and pediatric patients affected by MDs were enrolled from Azienda Ospedaliera Universitaria Pisana, Pisa, Italy (Institution 1) and the IRCCS Stella Maris Foundation, Calambrone-Pisa, Italy (Institution 2), respectively. All patients underwent a bilateral thighs MRI including an axial T1 weighted in- and out-of-phase (dual-echo). Both muscles and SAT were manually and separately segmented on out-of-phase image sets by a radiologist with 6 years of experience in musculoskeletal imaging. A U-Net1 and U-Net3 were built to automatically segment the SAT, all the thigh muscles together and the three muscular compartments separately. The dataset was randomly split into the on train, validation, and test set. The segmentation performance was assessed through the Dice similarity coefficient (DSC). The final cohort included 23 patients. The estimated DSC for U-Net1 was 96.8%, 95.3%, and 95.6% on train, validation, and test set, respectively, while the estimated accuracy for U-Net3 was 94.1%, 92.9%, and 93.9%. Both of the U-Nets achieved a median DSC of 0.95 for SAT segmentation. The U-Net1 and the U-Net3 achieved an optimal agreement with manual segmentation for the automatic segmentation. The so-developed neural networks have the potential to automatically segment thigh muscles and SAT in patients affected by MDs.
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Purpose To evaluate the reproducibility of radiomics features extracted from T2-weighted MR images in patients with neuroblastoma. Materials and Methods A retrospective study included 419 patients (mean age, 29 months ± 34 [SD]; 220 male, 199 female) with neuroblastic tumors diagnosed between 2002 and 2023, within the scope of the PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (ie, PRIMAGE) project, involving 746 T2/T2*-weighted MRI sequences at diagnosis and/or after initial chemotherapy. Images underwent processing steps (denoising, inhomogeneity bias field correction, normalization, and resampling). Tumors were automatically segmented, and 107 shape, first-order, and second-order radiomics features were extracted, considered as the reference standard. Subsequently, the previous image processing settings were modified, and volumetric masks were applied. New radiomics features were extracted and compared with the reference standard. Reproducibility was assessed using the concordance correlation coefficient (CCC); intrasubject repeatability was measured using the coefficient of variation (CoV). Results When normalization was omitted, only 5% of the radiomics features demonstrated high reproducibility. Statistical analysis revealed significant changes in the normalization and resampling processes (P < .001). Inhomogeneities removal had the least impact on radiomics (83% of parameters remained stable). Shape features remained stable after mask modifications, with a CCC greater than 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with a radiomics features stability of 70%. Only 7% of second-order radiomics features showed an excellent CoV of less than 0.10. Conclusion Modifications in the T2-weighted MRI preparation process in patients with neuroblastoma resulted in changes in radiomics features, with normalization identified as the most influential factor for reproducibility. Inhomogeneities removal had the least impact on radiomics features. Keywords: Pediatrics, MR Imaging, Oncology, Radiomics, Reproducibility, Repeatability, Neuroblastic Tumors Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Safdar and Galaria in this issue.
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Imagen por Resonancia Magnética , Neuroblastoma , Humanos , Neuroblastoma/diagnóstico por imagen , Neuroblastoma/patología , Masculino , Femenino , Estudios Retrospectivos , Imagen por Resonancia Magnética/métodos , Reproducibilidad de los Resultados , Preescolar , Niño , Lactante , Interpretación de Imagen Asistida por Computador/métodos , RadiómicaRESUMEN
Introduction: Despite the progress made in multidisciplinary care, there has been little improvement in the oncologic outcomes of oral cavity squamous cell carcinomas (OSCCs). In the latest edition of the TNM staging, "depth of invasion" (DOI) has recently been introduced as one of the criteria for determining the T stage, alongside other factors. DOI is widely recognized as an independent risk factor for nodal metastases and is a crucial consideration in the preoperative staging of OSCCs, along with measurements of tumor thickness (TT). While various diagnostic methods exist for assessing DOI, intraoral ultrasonography (IOUS) has gained popularity for its efficacy in evaluating OSCCs. Methods: This study sought to evaluate the diagnostic accuracy and reliability of ultrahigh-frequency ultrasound (UHFUS) in assessing oral cavity lesions compared to histopathological analysis. Results: The results revealed strong reliability in ultrasonographic measurements (ICC TT: 0.94; ICC DOI: 0.97) and distinct ultrasonographic features specific to different oral pathologies. This highlights the potential of UHFUS as a non-invasive imaging tool for precise diagnostic evaluations. Conclusions: Despite limitations such as a small sample size and focus on specific lesions, these promising results suggest that UHFUS could significantly enhance oral lesion diagnostics. Further research involving larger cohorts is necessary to validate and build upon these initial findings.
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PURPOSE: To evaluate the diagnostic accuracy of computed tomography (CT)-based radiomic algorithms and deep learning models to preoperatively identify lymph node metastasis (LNM) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: PubMed, CENTRAL, Scopus, Web of Science and IEEE databases were searched to identify relevant studies published up until February 11, 2024. Two reviewers screened all papers independently for eligibility. Studies reporting the accuracy of CT-based radiomics or deep learning models for detecting LNM in PDAC, using histopathology as the reference standard, were included. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2, the Radiomics Quality Score (RQS) and the the METhodological RadiomICs Score (METRICS). Overall sensitivity (SE), specificity (SP), diagnostic odds ratio (DOR), and the area under the curve (AUC) were calculated. RESULTS: Four radiomics studies comprising 213 patients and four deep learning studies with 272 patients were included. The average RQS total score was 12.00 ± 3.89, corresponding to an RQS percentage of 33.33 ± 10.80, while the average METRICS score was 63.60 ± 10.88. A significant and strong positive correlation was found between RQS and METRICS (p = 0.016; r = 0.810). The pooled SE, SP, DOR, and AUC of all the studies were 0.83 (95 %CI = 0.77-0.88), 0.76 (95 %CI = 0.62-0.86), 15.70 (95 %CI = 8.12-27.50) and 0.85 (95 %CI = 0.77-0.88). Meta-regression analysis results indicated that neither the study type (radiomics vs deep learning) nor the dataset size of the studies had a significant effect on the DOR (p = 0.09 and p = 0.26, respectively). CONCLUSION: Based on our meta-analysis findings, preoperative CT-based radiomics algorithms and deep learning models demonstrate favorable performance in predicting LNM in patients with PDAC, with a strong correlation between RQS and METRICS of the included studies.
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Carcinoma Ductal Pancreático , Aprendizaje Profundo , Metástasis Linfática , Neoplasias Pancreáticas , Tomografía Computarizada por Rayos X , Humanos , Carcinoma Ductal Pancreático/diagnóstico por imagen , Carcinoma Ductal Pancreático/patología , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/patología , Tomografía Computarizada por Rayos X/métodos , Metástasis Linfática/diagnóstico por imagen , Estadificación de Neoplasias , Cuidados Preoperatorios/métodos , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , RadiómicaRESUMEN
Pediatric sarcomas, rare malignancies of mesenchymal origin, pose diagnostic and therapeutic challenges. In this review, we explore the role of radiomics in reshaping our understanding of pediatric sarcomas, emphasizing methodological considerations and applications such as diagnostics and predictive modeling. A systematic review conducted up to November 2023 identified 72 papers on radiomics analysis in pediatric sarcoma from PubMed/MEDLINE, Web of Knowledge, and Scopus. Following inclusion and exclusion criteria, 10 reports were included in this review. The studies, predominantly retrospective, focus on Ewing sarcoma and osteosarcoma, utilizing diverse imaging modalities, including CT, MRI, PET/CT, and PET/MRI. Manual segmentation is common, with a median of 35 features extracted. Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS) assessments reveal a consistent emphasis on non-radiomic features, validation criteria, and improved methodological rigor in recent publications. Diagnostic applications dominate, with innovative studies exploring prognostic and treatment response aspects. Challenges include feature heterogeneity and sample size variations. The evolving landscape underscores the need for standardized methodologies. Despite challenges, the diagnostic and predictive potential of radiomics in pediatric oncology is evident, paving the way for precision medicine advancements.
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Purpose: Clinical evidence suggests an association between comorbidities and outcome in patients with glioblastoma (GBM). We hypothesised that the internal carotid artery (ICA) calcium score could represent a promising prognostic biomarker in a competing risk analysis in patients diagnosed with GBM. Methods: We validated the use of the ICA calcium score as a surrogate marker of the coronary calcium score in 32 patients with lung cancer. Subsequently, we assessed the impact of the ICA calcium score on overall survival in GBM patients treated with radio-chemotherapy. Results: We analysed 50 GBM patients. At the univariate analysis, methyl-guanine-methyltransferase gene (MGMT) promoter methylation (p = 0.048), gross total tumour resection (p = 0.017), and calcium score (p = 0.011) were significant prognostic predictors in patients with GBM. These three variables also maintained statistical significance in the multivariate analysis. Conclusions: the ICA calcium score could be a promising prognostic biomarker in GBM patients.
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Mounier-Kuhn syndrome is a rare airway disease characterized by tracheal and bronchial dilatation, primarily affecting middle-aged men. We present a case of Mounier-Kuhn syndrome in a 40-year-old man with a history of recurrent respiratory infections since adolescence. The diagnostic journey involved a multidisciplinary approach incorporating clinical evaluation, radiological imaging, and bronchoscopy. Computed tomography findings, including maximum intensity projection reconstructions and 3D rendering, facilitated the diagnosis by revealing significant airway dilation and associated abnormalities. Treatment primarily focused on supportive measures, including antibiotic therapy and respiratory physiotherapy. This case underscores the importance of considering Mounier-Kuhn syndrome in patients with recurrent respiratory infections and highlights the role of advanced imaging techniques in diagnosis.
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Introduction: Immune checkpoint inhibitors (ICIs) represent the standard therapy for metastatic melanoma. However, a few patients do not respond to ICIs and reliable predictive biomarkers are needed. Methods: This pilot study investigates the association between mRNA levels of programmed cell death-1 (PD-1) ligand 1 (PD-L1), interferon-gamma (IFN-γ), and transforming growth factor-ß (TGF-ß) in circulating extracellular vesicles (EVs) and survival in 30 patients with metastatic melanoma treated with first line anti-PD-1 antibodies. Blood samples were collected at baseline and RNA extracted from EVs; the RNA levels of PD-L1, IFN-γ, and TGF-ß were analysed by digital droplet PCR (ddPCR). A biomarker-radiomic correlation analysis was performed in a subset of patients. Results: Patients with high TGF-ß expression (cut-off fractional abundance [FA] >0.19) at baseline had longer median progression-free survival (8.4 vs. 1.8 months; p = 0.006) and overall survival (17.9 vs. 2.63 months; p = 0.0009). Moreover, radiomic analysis demonstrated that patients with high TGF-ß expression at baseline had smaller lesions (2.41 ± 3.27 mL vs. 42.79 ± 101.08 mL, p < 0.001) and higher dissimilarity (12.01 ± 28.23 vs. 5.65 ± 8.4; p = 0.018). Discussion: These results provide evidence that high TGF-ß expression in EVs is associated with a better response to immunotherapy. Further investigation on a larger patient population is needed to validate the predictive power of this potential biomarker of response to ICIs.
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BACKGROUND: To quantitatively evaluate CT lung abnormalities in COVID-19 survivors from the acute phase to 24-month follow-up. Quantitative CT features as predictors of abnormalities' persistence were investigated. METHODS: Patients who survived COVID-19 were retrospectively enrolled and underwent a chest CT at baseline (T0) and 3 months (T3) after discharge, with pulmonary function tests (PFTs). Patients with residual CT abnormalities repeated the CT at 12 (T12) and 24 (T24) months after discharge. A machine-learning-based software, CALIPER, calculated the CT percentage of the whole lung of normal parenchyma, ground glass (GG), reticulation (Ret), and vascular-related structures (VRSs). Differences (Δ) were calculated between time points. Receiver operating characteristic (ROC) curve analyses were performed to test the baseline parameters as predictors of functional impairment at T3 and of the persistence of CT abnormalities at T12. RESULTS: The cohort included 128 patients at T0, 133 at T3, 61 at T12, and 34 at T24. The GG medians were 8.44%, 0.14%, 0.13% and 0.12% at T0, T3, T12 and T24. The Ret medians were 2.79% at T0 and 0.14% at the following time points. All Δ significantly differed from 0, except between T12 and T24. The GG and VRSs at T0 achieved AUCs of 0.73 as predictors of functional impairment, and area under the curves (AUCs) of 0.71 and 0.72 for the persistence of CT abnormalities at T12. CONCLUSIONS: CALIPER accurately quantified the CT changes up to the 24-month follow-up. Resolution mostly occurred at T3, and Ret persisting at T12 was almost unchanged at T24. The baseline parameters were good predictors of functional impairment at T3 and of abnormalities' persistence at T12.
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Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.
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Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterize individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice. Digital biobanks can catalyze this process, facilitating the sharing of curated and standardized imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalized data-driven diagnostic approach in disease management and fostering the development of computational predictive models. This work aims to frame this perspective, first by evaluating the state of standardization of individual diagnostic domains and then by identifying challenges and proposing a possible solution towards an integrative approach that can guarantee the suitability of information that can be shared through a digital biobank. Our analysis of the state of the art shows the presence and use of reference standards in biobanks and, generally, digital repositories for each specific domain. Despite this, standardization to guarantee the integration and reproducibility of the numerical descriptors generated by each domain, e.g. radiomic, pathomic and -omic features, is still an open challenge. Based on specific use cases and scenarios, an integration model, based on the JSON format, is proposed that can help address this problem. Ultimately, this work shows how, with specific standardization and promotion efforts, the digital biobank model can become an enabling technology for the comprehensive study of diseases and the effective development of data-driven technologies at the service of precision medicine.
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Bancos de Muestras Biológicas , Medicina de Precisión , Humanos , Reproducibilidad de los Resultados , GenómicaRESUMEN
OBJECTIVES: To assess radiologists' current use of, and opinions on, structured reporting (SR) in oncologic imaging, and to provide recommendations for a structured report template. MATERIALS AND METHODS: An online survey with 28 questions was sent to European Society of Oncologic Imaging (ESOI) members. The questionnaire had four main parts: (1) participant information, e.g., country, workplace, experience, and current SR use; (2) SR design, e.g., numbers of sections and fields, and template use; (3) clinical impact of SR, e.g., on report quality and length, workload, and communication with clinicians; and (4) preferences for an oncology-focused structured CT report. Data analysis comprised descriptive statistics, chi-square tests, and Spearman correlation coefficients. RESULTS: A total of 200 radiologists from 51 countries completed the survey: 57.0% currently utilized SR (57%), with a lower proportion within than outside of Europe (51.0 vs. 72.7%; p = 0.006). Among SR users, the majority observed markedly increased report quality (62.3%) and easier comparison to previous exams (53.5%), a slightly lower error rate (50.9%), and fewer calls/emails by clinicians (78.9%) due to SR. The perceived impact of SR on communication with clinicians (i.e., frequency of calls/emails) differed with radiologists' experience (p < 0.001), and experience also showed low but significant correlations with communication with clinicians (r = - 0.27, p = 0.003), report quality (r = 0.19, p = 0.043), and error rate (r = - 0.22, p = 0.016). Template use also affected the perceived impact of SR on report quality (p = 0.036). CONCLUSION: Radiologists regard SR in oncologic imaging favorably, with perceived positive effects on report quality, error rate, comparison of serial exams, and communication with clinicians. CLINICAL RELEVANCE STATEMENT: Radiologists believe that structured reporting in oncologic imaging improves report quality, decreases the error rate, and enables better communication with clinicians. Implementation of structured reporting in Europe is currently below the international level and needs society endorsement. KEY POINTS: ⢠The majority of oncologic imaging specialists (57% overall; 51% in Europe) use structured reporting in clinical practice. ⢠The vast majority of oncologic imaging specialists use templates (92.1%), which are typically cancer-specific (76.2%). ⢠Structured reporting is perceived to markedly improve report quality, communication with clinicians, and comparison to prior scans.
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Actitud del Personal de Salud , Neoplasias , Radiólogos , Sociedades Médicas , Humanos , Europa (Continente) , Encuestas y Cuestionarios , Neoplasias/diagnóstico por imagen , Radiólogos/estadística & datos numéricos , Sistemas de Información Radiológica/estadística & datos numéricosRESUMEN
Our radiology department conducted an assessment of 300 neonatal radiographs in the neonatal intensive care unit over almost two years. The purpose was to evaluate the correct positioning of intravascular venous catheters. Our case series revealed that out of a total of 95 cases with misplaced devices, 59 were umbilical venous catheters and 36 were peripherally inserted central catheters. However, all of the central venous catheters were found to be properly positioned. Misplacements of neonatal intravascular devices were found to occur more frequently than expected. The scientific literature contains several articles highlighting the potential complications associated with misplaced devices. Our goal is to highlight the potential misplacements and associated complications that radiologists may encounter while reviewing conventional radiology imaging. Based on our experience, which primarily involved placing UVCs and PICCs, we discovered that conventional radiology is the most effective method for assessing proper device placement with the lowest possible radiation exposure. Given the high number of neonatal vascular device placement procedures, it is essential for radiologists to maintain a high level of vigilance and stay updated on the latest developments in this field.
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Purpose To perform a systematic review and meta-analysis assessing the predictive accuracy of radiomics in the noninvasive determination of isocitrate dehydrogenase (IDH) status in grade 4 and lower-grade diffuse gliomas. Materials and Methods A systematic search was performed in the PubMed, Scopus, Embase, Web of Science, and Cochrane Library databases for relevant articles published between January 1, 2010, and July 7, 2021. Pooled sensitivity and specificity across studies were estimated. Risk of bias was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2, and methods were evaluated using the radiomics quality score (RQS). Additional subgroup analyses were performed according to tumor grade, RQS, and number of sequences used (PROSPERO ID: CRD42021268958). Results Twenty-six studies that included 3280 patients were included for analysis. The pooled sensitivity and specificity of radiomics for the detection of IDH mutation were 79% (95% CI: 76, 83) and 80% (95% CI: 76, 83), respectively. Low RQS scores were found overall for the included works. Subgroup analyses showed lower false-positive rates in very low RQS studies (RQS < 6) (meta-regression, z = -1.9; P = .02) compared with adequate RQS studies. No substantial differences were found in pooled sensitivity and specificity for the pure grade 4 gliomas group compared with the all-grade gliomas group (81% and 86% vs 79% and 79%, respectively) and for studies using single versus multiple sequences (80% and 77% vs 79% and 82%, respectively). Conclusion The pooled data showed that radiomics achieved good accuracy performance in distinguishing IDH mutation status in patients with grade 4 and lower-grade diffuse gliomas. The overall methodologic quality (RQS) was low and introduced potential bias. Keywords: Neuro-Oncology, Radiomics, Integration, Application Domain, Glioblastoma, IDH Mutation, Radiomics Quality Scoring Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Glioblastoma , Glioma , Humanos , Isocitrato Deshidrogenasa/genética , Radiómica , Glioma/diagnóstico por imagen , MutaciónRESUMEN
Pleural mesothelioma (PM) is an aggressive disease that has a strong causal relationship with asbestos exposure and represents a major challenge from both a diagnostic and therapeutic viewpoint. Despite recent improvements in patient care, PM typically carries a poor outcome, especially in advanced stages. Therefore, a timely and effective diagnosis taking advantage of currently available imaging techniques is essential to perform an accurate staging and dictate the most appropriate treatment strategy. Our aim is to provide a brief, but exhaustive and up-to-date overview of the role of multimodal medical imaging in the management of PM.
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Mesotelioma , Neoplasias Pleurales , Humanos , Estadificación de Neoplasias , Mesotelioma/diagnóstico por imagen , Mesotelioma/etiología , Neoplasias Pleurales/diagnóstico por imagen , Neoplasias Pleurales/patología , Factores de Riesgo , Imagen MultimodalRESUMEN
In hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) extent ≥15% of left ventricular mass is considered a prognostic risk factor. LGE extent increases over time and the clinical role of the progression of LGE over time (LGE rate) was not prospectively evaluated. We sought to evaluate the prognostic role of the LGE rate in HCM. We enrolled 105 patients with HCM who underwent cardiac magnetic resonance (CMR) at baseline (CMR-I) and after ≥2 years of follow-up (CMR-II). LGE rate was defined as the ratio between the increase of LGE extent (grams) and the time interval (months) between examinations. A combined end point of sudden cardiac death, resuscitated cardiac arrest, appropriate Implanted Cardioverter Defibrillator (ICD) intervention, and sustained ventricular tachycardia was used (hard events). The percentage of patients with LGE extent ≥15% increased from 9% to 20% from CMR-I to CMR-II (p = 0.03). During a median follow-up of 52 months, 25 hard events were recorded. The presence of LGE ≥15% at CMR-II allowed a significant reclassification of the risk of patients than at LGE ≥15% at CMR-I (net reclassification improvement 0.21, p = 0.046). On the MaxStat analysis, the optimal prognostic cut point for LGE rate was >0.07 g/month. On the Kaplan-Meier curve, patients with LGE rate >0.07 had worse prognosis than those without (p <0.0001). LGE rate >0.07 allowed a significant reclassification of the risk compared with LGE ≥15% at CMR-I and at CMR-II (net reclassification improvement 0.49, p = 0.003). In the multivariable models, LGE rate >0.07 was the best independent predictor of hard events. In conclusion, CMR should be repeated after 2 years to reclassify the risk for sudden death of those patients. A high LGE rate may be considered a novel prognostic factor in HCM.
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Cardiomiopatía Hipertrófica , Medios de Contraste , Humanos , Pronóstico , Medios de Contraste/farmacología , Gadolinio/farmacología , Cardiomiopatía Hipertrófica/diagnóstico por imagen , Cardiomiopatía Hipertrófica/patología , Corazón , Factores de Riesgo , Muerte Súbita Cardíaca/epidemiología , Muerte Súbita Cardíaca/etiología , Muerte Súbita Cardíaca/prevención & control , Imagen por Resonancia Cinemagnética , Valor Predictivo de las PruebasRESUMEN
Given the expanding indications toward younger patients at lower surgical risk, transcatheter aortic valve replacement (TAVR) simplification and streamlining are gaining increasing importance. Patients who underwent TAVR from the year 2015 to 2020 were prospectively enrolled. The patients were divided in time tertiles according to the date of intervention. Data on preprocedural planning, including coronary computed tomography angiography (CCTA), procedures, and outcomes, were compared between the time tertiles. A total of 771 consecutive patients from a single institution were enrolled. We observed a trend toward the use of a fully percutaneous versus surgical approach for the index access, left radial artery versus contralateral femoral artery for the secondary access, and left ventricular pacing on the stiff guidewire versus right ventricular pacing. Immediate device success significantly increased, whereas the length of hospital stay decreased. Overall, approximately 60% of the total study population underwent CCTA instead of coronary angiography, with no adverse events. One-year survival rates significantly improved over time. A simplified TAVR approach was associated with better survival, whereas low baseline functional capacity, preexisting coronary artery disease, renal impairment, periprocedural blood transfusions, and paravalvular leak were related to worse outcomes. In conclusion, our study showed a constant tendency to procedure streamlining and improve procedural success and 1-year outcomes. A strategy based on CCTA allows sparing safely almost half of the preoperative invasive coronary angiography.
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Estenosis de la Válvula Aórtica , Reemplazo de la Válvula Aórtica Transcatéter , Humanos , Reemplazo de la Válvula Aórtica Transcatéter/métodos , Válvula Aórtica/cirugía , Resultado del Tratamiento , Factores de Riesgo , Angiografía Coronaria , Estudios RetrospectivosRESUMEN
OBJECTIVES: To present the results of a survey on the assessment of treatment response with imaging in oncologic patient, in routine clinical practice. The survey was promoted by the European Society of Oncologic Imaging to gather information for the development of reporting models and recommendations. METHODS: The survey was launched on the European Society of Oncologic Imaging website and was available for 3 weeks. It consisted of 5 sections, including 24 questions related to the following topics: demographic and professional information, methods for lesion measurement, how to deal with diminutive lesions, how to report baseline and follow-up examinations, which previous studies should be used for comparison, and role of RECIST 1.1 criteria in the daily clinical practice. RESULTS: A total of 286 responses were received. Most responders followed the RECIST 1.1 recommendations for the measurement of target lesions and lymph nodes and for the assessment of tumor response. To assess response, 48.6% used previous and/or best response study in addition to baseline, 25.2% included the evaluation of all main time points, and 35% used as the reference only the previous study. A considerable number of responders used RECIST 1.1 criteria in daily clinical practice (41.6%) or thought that they should be always applied (60.8%). CONCLUSION: Since standardized criteria are mainly a prerogative of clinical trials, in daily routine, reporting strategies are left to radiologists and oncologists, which may issue local and diversified recommendations. The survey emphasizes the need for more generally applicable rules for response assessment in clinical practice. CRITICAL RELEVANCE STATEMENT: Compared to clinical trials which use specific criteria to evaluate response to oncological treatments, the free narrative report usually adopted in daily clinical practice may lack clarity and useful information, and therefore, more structured approaches are needed. KEY POINTS: · Most radiologists consider standardized reporting strategies essential for an objective assessment of tumor response in clinical practice. · Radiologists increasingly rely on RECIST 1.1 in their daily clinical practice. · Treatment response evaluation should require a complete analysis of all imaging time points and not only of the last.
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Prognosis in advanced gastric cancer (aGC) is predicted by clinical factors, such as stage, performance status, metastasis location, and the neutrophil-to-lymphocyte ratio. However, the role of body composition and sarcopenia in aGC survival remains debated. This study aimed to evaluate how abdominal visceral and subcutaneous fat volumes, psoas muscle volume, and the visceral-to-subcutaneous (VF/SF) volume ratio impact overall survival (OS) and progression-free survival (PFS) in aGC patients receiving first-line palliative chemotherapy. We retrospectively examined CT scans of 65 aGC patients, quantifying body composition parameters (BCPs) in 2D and 3D. Normalized 3D BCP volumes were determined, and the VF/SF ratio was computed. Survival outcomes were analyzed using the Cox Proportional Hazard model between the upper and lower halves of the distribution. Additionally, response to first-line chemotherapy was compared using the χ2 test. Patients with a higher VF/SF ratio (N = 33) exhibited significantly poorer OS (p = 0.02) and PFS (p < 0.005) and had a less favorable response to first-line chemotherapy (p = 0.033), with a lower Disease Control Rate (p = 0.016). Notably, absolute BCP measures and sarcopenia did not predict survival. In conclusion, radiologically assessed VF/SF volume ratio emerged as a robust and independent predictor of both survival and treatment response in aGC patients.